Electrospun FeN@CNT single-atom nanozyme for triple-mode ROS-mediated colorimetric and fluorometric detection of vitamin C

Electrospun FeN@CNT single-atom nanozyme for triple-mode ROS-mediated colorimetric and fluorometric detection of vitamin C | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Electrospun FeN@CNT single-atom nanozyme for triple-mode ROS-mediated colorimetric and fluorometric detection of vitamin C Ali M. Alaseem, Razan Orfali, Glowi Alasiri, Ramadan Ali, Al-Montaser Bellah H. Ali, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8969133/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Accurate vitamin C quantification is essential for evaluating nutritional status and supporting clinical assessment of deficiency risk, oxidative stress, and supplementation outcomes, while also enabling quality control of foods and pharmaceuticals by verifying label claims and monitoring vitamin C degradation during processing and storage. Here, we report a highly sensitive dual-mode (colorimetric/fluorometric) sensing platform based on iron–nitrogen co-doped carbon nanotubes (FeN@CNTs) prepared via electrospinning, hydrothermal treatment, and carbonization. The resulting single-atom nanozyme contains atomically dispersed Fe–Nₓ catalytic sites that emulate peroxidase-like activity and deliver strong catalytic performance. The assay exploits reactive oxygen species (ROS)-driven oxidation of a chromogenic reporter (TMB) and a fluorogenic reporter (Amplex Red), while vitamin C is quantified through its antioxidant/ROS-scavenging effect that suppresses signal formation in a concentration-dependent manner. Under optimized conditions, the platform achieves ultralow detection limits of 0.042 µM (colorimetric) and 0.003 µM (fluorometric), broad linearity up to 360 µM, and high analytical precision (RSD < 5%). A smartphone-assisted RGB readout further enables rapid, portable quantification suitable for on-site screening. The FeN@CNTs sensor demonstrates strong operational stability, high selectivity, and good tolerance toward common interferents, including biothiols and polyphenols. Practical feasibility was confirmed in pharmaceutical tablets, fruit juices, and urine, affording recoveries of 94.5–107.7% and results statistically consistent with a reference HPLC method. Collectively, these outcomes position FeN@CNTs as a robust single-atom nanozyme platform for real-time vitamin C analysis with potential impact in food safety surveillance, clinical testing, and point-of-care sensing. Single-atom nanozyme FeN@CNTs Dual-mode sensing Vitamin C detection Colorimetric and fluorometric assay Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Vitamin C is an essential water-soluble antioxidant that exhibits strong reducing capability and plays a pivotal role in maintaining redox homeostasis and supporting fundamental metabolic processes in the human body [ 1 ]. Insufficient levels of vitamin C impair collagen biosynthesis and compromise cellular structural integrity, which can precipitate pathological conditions including immune dysfunction, scurvy, cardiovascular disorders, and anemia [ 2 – 4 ]. Although most mammals are capable of synthesizing vitamin C endogenously, humans lack this ability and must therefore rely on dietary intake [ 5 , 6 ], which has driven its extensive utilization in the food and pharmaceutical industries. Beyond its nutritional significance, vitamin C exhibits strong free-radical scavenging activity and tyrosinase inhibition, underpinning its widespread application in cosmetic formulations aimed at antioxidative protection and skin-whitening effects [ 7 ]. Nevertheless, excessive intake of vitamin C may elicit adverse health effects, including nephrolithiasis, diarrhea, and gastrointestinal discomfort [ 8 , 9 ]. Consequently, the development of simple, accurate, and reliable analytical methods for vitamin C determination is of considerable importance for food safety, quality control, and related application domains. To date, numerous analytical methods have been used to quantify vitamin C, such as HPLC [ 10 ], capillary electrophoresis [ 11 ], LC/MS [ 12 ], and electrochemical voltammetry [ 13 ]. Although chromatographic techniques provide excellent sensitivity and precision, they typically involve expensive operation, lengthy sample preparation and analysis, and sophisticated instrumentation [ 14 , 15 ]. Electrochemical methods, in contrast, provide a cost-effective and sensitive alternative; however, they are frequently hindered by challenges such as electrode fouling, limited selectivity, and interference from coexisting species [ 16 , 17 ]. By comparison, colorimetric and fluorometric methods offer several advantages, including low cost, ease of visualization, good accuracy, and simple operation, making them particularly suitable for rapid and on-site analysis. Artificial nanomaterial-based enzymes, commonly referred to as nanozymes, have emerged as a versatile and promising alternative to natural enzymes due to their tunable structures, high stability, and cost-effectiveness [ 18 , 19 ]. By emulating the catalytic mechanisms of natural enzymes, nanozymes can exhibit significant catalytic activity [ 20 ]. Over the past decade, substantial research efforts have broadened the diversity of nanozymes, facilitating their applications in catalysis, biomedical therapy, environmental remediation, tissue engineering, and biosensing [ 21 – 24 ]. Nonetheless, the relatively modest catalytic efficiency of many nanozymes continues to limit their full potential and widespread practical deployment. Strategies to enhance nanozyme activity typically focus on tuning particle size and morphology, engineering specific crystal facets, and modulating surface charge and composition [ 25 ]. However, many nanozymes continue to display limited catalytic performance, primarily due to unevenly distributed active sites and suboptimal atomic utilization [ 26 ]. This challenge has spurred interest in designing nanozymes with highly abundant, well-defined active centers. In this context, single-atom catalysts (SACs), first reported in 2011, have attracted considerable attention owing to their exceptional catalytic efficiency, maximized atomic utilization, and cost-effective performance in catalysis and energy-related applications [ 27 ]. Single-atom catalysts (SACs), created by immobilizing individual metal atoms on solid supports, combine distinctive geometric and electronic characteristics with atomically defined active sites and nearly complete metal-atom utilization [ 28 , 29 ]. Notably, nitrogen-doped carbon frameworks containing M–N–C motifs can host atomically dispersed metals as M–Nx sites, which closely resemble the active centers found in natural enzymes [ 30 , 31 ]. This approach has led to the emergence of single-atom nanozymes (SAzymes) with outstanding catalytic activity. In addition, the uniformity and clear definition of SAzyme active sites make it possible to systematically probe structure–activity relationships and reaction pathways, offering important guidance for rational catalyst design [ 32 , 33 ]. Various strategies have been developed for the synthesis of SAzymes, including atomic layer deposition, impregnation, and coprecipitation, all of which rely on the precise arrangement of environmental atoms and defect sites in supports such as metal–organic frameworks (MOFs) [ 34 , 35 ] and nitrogen-doped carbon materials [ 36 , 37 ]. Despite these advancements, these methods often struggle to fully prevent metal atom aggregation during high-temperature pyrolysis, frequently necessitating additional acid-etching treatments. Furthermore, the formation of single-atom sites is typically random, resulting in limited reproducibility and challenges for large-scale, uniform production [ 38 , 39 ]. In this study, iron- and nitrogen-co-doped carbon nanotube catalysts (Fe,N@CNTs) were fabricated via electrospinning and hydrothermal treatment followed by carbonization. The synthesis was designed to maximize the utilization of single-atom Fe sites, thereby enhancing enzyme-mimicking catalytic activity. Initially, a tubular polypyrrole structure was constructed, which subsequently enables the in situ formation of highly active Fe–N–C sites within the carbon matrix ( Scheme 1 ). The resulting Fe, N@CNTs exhibit remarkable peroxidase-like activity, attributed to the synergistic effects of well-defined Fe–N–C active sites and the tubular architecture, which facilitate efficient electron transfer and mass transport. Furthermore, these catalysts are employed as a dual-mode platform for both colorimetric and fluorometric detection of vitamin C, demonstrating their potential for sensitive and reliable analytical applications. 2. Experimental 2.1. Materials and reagents Reagents and chemicals were sourced as follows. From Sigma-Aldrich (Germany), we obtained vitamin C (99.4%), glutathione (GSH, 98.7%), 3,3′,5,5′-tetramethylbenzidine (TMB), pyrrole (98.8%), 5,5-dimethyl-1-pyrroline-N-oxide (DMPO), 1,4-benzoquinone (PBQ; 97.9%), isopropyl alcohol (IPA, 99.5%), thiourea (99.7%), Amplex Red (AR, 98.7%), terephthalic acid (TA, 99.0%), L-histidine (L-His, 98.7%), thiourea (ThU, 99.8%), furfuryl alcohol (FA, AR), glucose (99.5%), uric acid (97.0%),, dopamine hydrochloride (97.4%), tryptophan (98.0%), cholesterol (98.9%), alanine (97.5%), cysteine (98.7%), Ferulic acid (98.9%), luteoin (98.0%), caffeic acid (99.4%), phenylalanine (98.4%), Gallic acid (99.8%), bovine serum albumin (BSA, 98.7%), and methionine (98.5%), and Polyacrylonitrile (PAN, Mw = 80,000) fibrils were purchased from Sigma-Aldrich (Germany). Additional reagents—hydrogen peroxide (H₂O₂, 30.0%), dimethylformamide (DMF), ammonium persulfate, acetic acid (CH₃COOH), boric acid (H₃BO₃), phosphoric acid (H₃PO₄), and ferric chloride hexahydrate (FeCl3•6H₂O)—were supplied by Merck (Germany). Deionized water was used in all experiments. 2.2. Instruments Comprehensive specifications of the instruments used, including calibration and operating parameters, are provided in the Supporting Information. 2.3. Preparation of FeN@CNTs Poly(pyrrole) nanofibers were prepared by electrospinning a 10.5 wt % PAN solution in DMF maintained at 100°C. Electrospinning was performed at an applied voltage of 22 kV with a 25 cm tip-to-collector distance. The resulting fibrous membrane (100 mg) was dispersed in deionized water (60 mL), followed by addition of pyrrole (200 µL). Oxidative polymerization was initiated by FeCl₃•6H₂O solution (5 mL, 50 mg mL⁻¹). The product was thoroughly washed and dried; a 30 mL portion of the dispersion was then subjected to hydrothermal treatment at 220°C to remove residual PAN, yielding Fe–poly(pyrrole) nanotubes. Finally, the nanotubes were carbonized at 800°C to obtain FeN@CNTs ( Scheme S1 ). As a control, N@CNTs were synthesized using an identical procedure, with ammonium persulfate replacing FeCl₃·6H₂O as the oxidant. 2.4. Steady-state kinetics Steady-state kinetics were used to quantify the nanozyme’s peroxidase-mimicking activity with TMB as the colorimetric substrate. Reactions were performed at constant H₂O₂ (25 mM) and TMB (0.4 mM), and the reaction kinetics were followed by recording the absorbance as a function of time. Initial rates (v) were extracted from the linear region of the absorbance–time traces and fitted to the Michaelis–Menten equation to obtain kinetic parameters. Apparent Km and V max were also derived from the Lineweaver–Burk plot using: Where V is the initial velocity, [S] is the substrate concentration, Km is the Michaelis constant, and V max is the maximum rate of the reaction. 2.5. Detection steps 2.5.1. Colorimetric method Vitamin C standards at different concentrations were incubated in BR buffer (pH 3.8). The reaction mixture was assembled by stepwise addition of H₂O₂ (200 µL, 2.8 mM), TMB (300 µL, 2.2 mM), and FeN@CNTs nanozyme dispersion (100 µL, 90 µg mL⁻¹), followed by dilution to a total volume of 1.0 mL with BR buffer (pH 3.8). The mixture was incubated at room temperature for 6 min, and the absorbance of oxidized TMB was measured at 650 nm. 2.5.2. Fluorometric method For fluorescence detection of vitamin C, reactions were prepared in BR buffer (pH 3.8) by sequentially mixing 200 µL of H₂O₂ (2.8 mM), 200 µL of Amplex Red (AR, 1.8 mM), and 100 µL of FeN@CNTs (90 µg mL⁻¹), followed by dilution to 1.0 mL with BR buffer. The mixture was incubated for 5 min at room temperature, and fluorescence was measured at 590 nm. 2.5.3. Smartphone-based detection To assess portability, both TMB and Amplex Red assays were adapted for smartphone-based detection. After the reaction, mixtures were transferred to a transparent 96-well plate. Images were captured using a smartphone camera (Infinix Pro 10) under consistent lighting, with the phone fixed ~ 15 cm above the sample. For colorimetric assays, blue-channel intensity (650 nm) was extracted using a Color Picker app. For fluorescence assays, a portable UV flashlight (365 nm) was used for excitation, and red-channel intensity (590 nm) was analyzed. A black enclosure was used to minimize ambient light interference. Extracted color intensities were plotted against vitamin C concentrations to generate standard calibration curves ( Scheme S2 ). 2.6. Real samples analysis A tablet powder sample (0.5 mg) was dissolved in 15 mL of ultrapure water. For fruit matrices (orange or tomato), 1.5 g of sample was homogenized with 2.5 mL of ultrapure water, followed by centrifugation at 10,000 rpm for 15 min; the resulting supernatant was then collected. Tablet solutions, fruit supernatants, and beverage samples were passed through a 0.45 µm filter and diluted with BR buffer (pH 3.8) prior to spiked recovery experiments. Vitamin C levels were determined using the FeN@CNTs nanozyme assay under the same conditions applied for the calibration standards. All analyses were conducted in triplicate, and results are reported as mean ± SD. Urine samples were diluted 10-fold with BR buffer (pH 3.8), spiked with vitamin C, and evaluated using the identical sensing protocol. 3. Results and discussions 3.1. Characterization The fabrication of FeN@CNTs is outlined in Scheme 1 . Briefly, PAN nanofibers (≈ 180.79 nm average diameter, Fig. 1 A) are first produced by electrospinning to serve as a uniform, high-surface-area scaffold that enables conformal coating and preserves 1D morphology during subsequent processing. Pyrrole is then adsorbed onto the PAN surface, followed by the introduction of Fe³⁺, which simultaneously acts as an oxidizing initiator for in situ polymerization and as a metal source to promote coordination with nitrogen functionalities. This step yields a Fe-containing poly(pyrrole) sheath anchored on the PAN fibers, creating precursor architecture designed to maximize the density and accessibility of Fe–Nₓ motifs after thermal conversion. As evidenced by SEM analysis, the Fe–PAN@polypyrrole nanofibers exhibit a significantly increased average diameter (~ 205.73 nm) compared with pristine PAN fibers (Fig. 1 B and D ), indicating the successful deposition of the Fe-containing polypyrrole layer. Subsequent hydrothermal treatment effectively removes the PAN core, resulting in dimensionally uniform FeN@CNTs. The hollow tubular morphology and structural uniformity of the resulting materials are clearly confirmed by both SEM and TEM observations (Fig. 1 C and E ). Elemental mapping of the FeN@CNTs confirms the homogeneous distribution of C, N, and Fe throughout the nanotube framework (Fig. 1 F–H), supporting successful incorporation of Fe within the nitrogen-containing carbon matrix. Quantitative inductively coupled plasma analysis further determines a Fe content of 1.08 wt%, which falls within the typical loading range reported for Fe-based single-atom catalysts and related Fe–N–C architectures [ 40 , 41 ]. The XRD profile of FeN@CNTs displays a single broad halo centered within 2θ ≈ 20–45° and lacks sharp Bragg reflections (Fig. 1 I), consistent with a predominantly turbostratic/amorphous carbon framework and the absence of detectable crystalline Fe-containing phases. While XRD cannot directly prove atomic dispersion, the featureless pattern—together with the lack of Fe/FeOx signatures—supports that iron is present below the XRD detection limit and/or incorporated as highly dispersed species. Raman spectra show the characteristic D band (~ 1373 cm⁻¹) and G band (~ 1584 cm⁻¹) (Fig. 1 J), confirming the coexistence of defect-rich and graphitized carbon domains. Notably, the rise in the I D /I G ratio upon Fe incorporation indicates an increased density of structural defects/edge sites, which can promote catalytic turnover by (i) creating additional adsorption/activation sites and (ii) providing coordination/anchoring environments (e.g., Fe–Nx motifs) that stabilize isolated Fe centers within the carbon lattice [ 14 , 15 ]. The chemical states of the constituent elements and the local Fe–N coordination in FeN@CNTs were interrogated using complementary X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) analyses. The XPS survey spectrum shows dominant signals from C, N, and O, while the Fe signal remains weak, as expected for the low Fe loading (Fig. 1 K). Deconvolution of the high-resolution C 1s spectrum (Fig. 1 L) yields components at 284.8 eV (C = C), 285.9 eV (C–N), and 287.4 eV (C–O), confirming the formation of a heteroatom-enriched carbon framework with substantial N incorporation [ 42 ]. The N 1s spectrum (Fig. 1 M) can be fitted with peaks centered at 396.2, 399.6, 400.7, and 401.2 eV, assigned to pyridinic N, pyrrolic N, graphitic N, and oxidized N, respectively [ 43 ]. Importantly, pyridinic and pyrrolic nitrogens are widely recognized as effective coordination/anchoring sites for isolated Fe species, facilitating the formation of Fe–Nx motifs and suppressing Fe aggregation, whereas graphitic N—embedded within the carbon basal plane—modulates charge density and electronic conductivity, thereby influencing catalytic kinetics. In the Fe 2p region (Fig. 1 N), the fitted peaks at 709.2, 714.5, and 721.3 eV correspond to Fe²⁺ 2p 3/2 , Fe³⁺ 2p 3/2 , and Fe²⁺ 2p 1/2 , respectively, indicating the coexistence of mixed-valence Fe species stabilized by the N-doped carbon matrix [ 44 ]. To elucidate the local coordination environment of Fe in FeN@CNTs, XAS was employed. As shown in Fig. 1 O, the absorption features are consistent with Fe existing in a positively charged state, which is commonly associated with coordination to electronegative N ligands in Fe–N–C architectures. In the Fourier-transformed EXAFS profile, FeN@CNTs exhibit a dominant first-shell peak at ~ 1.47 Å, assignable to Fe–N scattering, whereas metallic Fe foil displays a characteristic Fe–Fe contribution at ~ 2.25 Å. Notably, the absence (or pronounced suppression) of Fe–Fe coordination in FeN@CNTs relative to Fe foil supports that Fe is present predominantly as isolated, single-site species rather than aggregated nanoparticles. Collectively, these XAS results substantiate the formation of atomically dispersed Fe–Nx moieties embedded within the N-doped carbon nanotube framework. Such single-site anchoring can maximize the accessibility of Fe centers and stabilize the active configuration under reaction conditions, providing a plausible structural basis for the enhanced catalytic performance observed for FeN@CNTs. [ 45 ]. Nitrogen adsorption–desorption measurements of FeN@CNTs typically show a type-IV isotherm with an evident hysteresis loop, indicating a mesoporous architecture arising from the hollow nanotube channels and inter-tube voids. A noticeable uptake at low relative pressure (P/P 0 < 0.1) suggests the presence of micropores introduced during carbonization/activation of the poly(pyrrole) framework. Overall, the resulting high specific surface area (~ 389.78 m² g⁻ 1 ) and hierarchical micro/mesoporosity provide abundant exposed/accessible Fe–Nx sites and facilitate rapid mass transport, which is favorable for catalytic performance (Fig. 1 P). 3.2. Peroxidase-mimic activity TMB is widely used as a chromogenic probe for benchmarking the peroxidase-like activity of nanozymes. Under acidic conditions, peroxidase-mimicking catalysts activate H₂O₂ to generate reactive oxygen species (ROS), primarily •OH andO₂•⁻, which subsequently oxidize colorless TMB to its blue charge-transfer product. The formation of oxTMB yields a distinct visible absorption band (typically centered around ~ 652 nm), allowing the catalytic reaction rate and overall activity to be quantified spectrophotometrically with high sensitivity. Upon H₂O₂ addition, a sharp rise in absorbance was observed, confirming the catalyst’s peroxidase-like behavior (Fig. 2 A). Notably, FeN@CNTs outperformed control materials, reflecting superior catalytic efficiency (Fig. 2 B). This performance arises from the combined effect of a highly porous carbon framework, which enhances reactant transport, and evenly distributed Fe–Nₓ sites, which catalyze H₂O₂ breakdown and ROS generation. These structural and electronic features together contribute to the exceptional activity of FeN@CNTs. Time-dependent kinetic measurements demonstrate that FeN@CNTs efficiently catalyze the oxidation of TMB, as reflected by the continuous increase in the characteristic absorbance at ~ 650 nm (Fig. 2 C). Relative to the corresponding control systems, FeN@CNTs produce a markedly steeper initial slope, indicating a substantially higher apparent catalytic rate. Notably, the absorbance–time profile remains linear during the first 300 s, suggesting that the reaction proceeds under kinetic control within this window. Accordingly, a fixed incubation time of 300 s was adopted as the standard reaction interval for subsequent activity comparisons and sensing measurements to ensure consistent quantification under the initial-rate regime. Michaelis–Menten kinetics were employed to quantify the intrinsic catalytic behavior of FeN@CNTs toward both H₂O₂ and TMB, and the corresponding Lineweaver–Burk plots are provided in Fig. S1 . The extracted parameters indicate a strong substrate affinity, with Km values of 1.87 mM for H₂O₂ and 0.176 mM for TMB, together with high maximal velocities (V max =20.17×10 − 8 and 18.02×10 − 8 M·s⁻¹ for H₂O₂ and TMB, respectively). Collectively, these kinetic metrics verify efficient peroxidase-like catalysis and compare favorably with representative Fe-based nanozymes reported in the literature ( Table S1 ). Mechanistically, the performance can be rationalized by the synergistic architecture: atomically dispersed Fe–Nx motifs provide accessible redox-active centers for H₂O₂ activation and electron transfer, whereas the conductive, porous CNT network facilitates reactant diffusion and enhances exposure of catalytic sites. This combination of high-affinity kinetics and structural accessibility supports the use of FeN@CNTs as a robust platform for catalytic assays and (bio)sensing readouts. To further corroborate the peroxidase-like activity of FeN@CNTs using an orthogonal readout, we employed a fluorometric assay based on Amplex Red (AR). In the presence of H₂O₂, FeN@CNTs catalyze the oxidation of AR to resorufin, generating a strong emission centered at ~ 590 nm upon excitation at 542 nm. As depicted in Fig. 2 D, the FeN@CNTs/H₂O₂/AR system produces a substantially higher fluorescence intensity as the corresponding control groups, evidencing more efficient H₂O₂ activation and substrate turnover. The quantitative comparison in Fig. 2 E confirms this enhancement and shows strong consistency with the activity trends obtained from the TMB colorimetric assay, indicating that the observed catalytic behavior is robust across independent detection modalities. Kinetic traces (Fig. 2 F) further demonstrate rapid AR oxidation catalyzed by FeN@CNTs, as reflected by the continuous increase in fluorescence at ~ 590 nm over time. The markedly steeper initial slope relative to controls highlights a higher apparent reaction rate. Importantly, the fluorescence response remains linear within the first 300 s, supporting that the reaction proceeds under initial-rate (kinetically controlled) conditions before substantial substrate depletion or product accumulation occurs. Therefore, a standardized incubation time of 300 s was selected for subsequent catalytic comparisons and sensing experiments to ensure reproducible quantification within the linear regime. 3.3. Detection mechanism EDTA was introduced as a chelating inhibitor to interrogate the nature of the catalytically active sites in FeN@CNTs. Upon EDTA addition, the catalytic response decreased sharply ( Fig. S1 A ), evidenced by a pronounced attenuation of the 650 nm absorbance. Given EDTA’s strong affinity for iron ions, this suppression is consistent with coordination of EDTA to the Fe centers, which competitively blocks substrate access and diminishes turnover. Collectively, the inhibition outcome supports that Fe-based sites are directly responsible for the observed peroxidase-like activity rather than the carbon framework alone. The peroxidase-mimicking performance of FeN@CNTs is attributed to the concerted effects of atomically coordinated Fe–Nₓ sites, abundant accessible surface area, and hierarchical pore channels that collectively accelerate reactant adsorption and mass transport. To identify the reactive oxygen species (ROS) involved, scavenger tests were conducted using thiourea (ThU, •OH quencher), p-benzoquinone (PBQ, •O₂⁻ quencher), and furfuryl alcohol/L-histidine (FA/L-His, ¹O₂ quenchers). In all cases, increasing scavenger concentration progressively suppressed the TMB oxidation signal at 650 nm ( Fig. S1 B ), confirming ROS participation in the catalytic pathway. Notably, the strongest inhibition was observed for ThU and PBQ, indicating that •OH and •O₂⁻ dominate the reaction mechanism, whereas ¹O₂ plays a comparatively minor role. Electron spin resonance (ESR) measurements with DMPO as a spin-trapping agent provided direct evidence for radical formation during catalysis. As shown in Fig. S1 C , the characteristic quartet pattern (1:2:2:1) corresponding to the DMPO–•OH adduct and the diagnostic DMPO–•O₂⁻ adduct signal were clearly observed, confirming that FeN@CNTs catalytically generate both •OH and •O₂⁻ species under the reaction conditions. These ESR results corroborate the scavenger experiments and support a radical-driven oxidation pathway. The FeN@CNTs/TA/H₂O₂ system produced a pronounced fluorescence enhancement, consistent with •OH-mediated oxidation of TA to the highly fluorescent 2-hydroxy TA, thereby confirming •OH formation during catalysis ( Fig. S1 D) . Complementary inhibition experiments further supported superoxide participation: introduction of superoxide dismutase (SOD) substantially suppressed the catalytic response, indicating that •O₂⁻ radicals are also generated and contribute to the overall peroxidase-like oxidation process ( Fig. S1 E) . Vitamin C suppresses peroxidase-mimicking nanozyme reactions through multiple, often concurrent pathways: (i) it consumes H₂O₂ via direct redox reaction, lowering the effective oxidant concentration; (ii) it scavenges ROS and/or reduces high-valent metal–oxo intermediates, thereby interrupting the catalytic cycle; (iii) it chemically reduces the oxidized chromogenic/fluorogenic reporter (e.g., oxTMB or resorufin) back to its reduced form, diminishing the analytical signal; and, in some systems, (iv) it adsorbs to or coordinates with catalytic centers, partially blocking active sites and modulating surface redox properties. 3.4. Optimization of conditions Catalytic assay parameters were systematically optimized by independently tuning pH, temperature, incubation time, FeN@CNTs loading, and substrate concentration to maximize signal intensity while preserving kinetic linearity. The nanozyme exhibited its highest apparent peroxidase-like activity at pH 3.8 in BR buffer, a condition that favors H₂O₂ activation and accelerates electron-transfer reactions on Fe–Nₓ sites ( Fig. S2A ). This acidic optimum is also advantageous analytically because it suppresses spontaneous background oxidation of the reporter in control systems, thereby improving the signal-to-noise ratio and the robustness of subsequent quantitative measurements [ 46 , 47 ]. FeN@CNTs retained more than 78% of its maximal catalytic activity across 20–60°C, indicating good thermal tolerance and enabling reliable operation without strict temperature control ( Fig. S2B ). The response increased monotonically with nanozyme dosage, consistent with a higher density of accessible Fe–Nₓ active sites and greater catalytic turnover. A working concentration of 90 µg mL⁻¹ was therefore selected as an optimal compromise between signal intensity, reagent consumption, and cost-effectiveness, while maintaining a clear dynamic range for quantitative measurements ( Fig. S2C ). Maximal chromogenic response was obtained at 2.2 mM TMB and 2.8 mM H₂O₂, reflecting an optimal balance between oxidant availability and substrate saturation while avoiding signal loss from over-oxidation and elevated background at higher concentrations ( Fig. S2D, E ). For the fluorometric pathway, the strongest emission was achieved using 2.8 mM H₂O₂ and 1.8 mM AR ( Fig. S2F ), consistent with efficient ROS-driven conversion of AR to its fluorescent product under the FeN@CNTs-catalyzed conditions. Notably, the shared optimum H₂O₂ level across both readouts indicates a common oxidant-controlled step in the catalytic cycle, supporting mechanistic consistency between the colorimetric and fluorescence modes. Collectively, these optimized parameters provide a robust operating window that improves signal-to-noise, minimizes run-to-run variability, and enables reproducible dual-mode sensing performance. 3.5. Quantitative parameters Vitamin C markedly suppressed FeN@CNTs-catalyzed TMB oxidation by consuming reactive oxygen species and/or reducing oxidized TMB back to its colorless form, leading to a concentration-dependent decrease in absorbance at 650 nm (Fig. 3 A). The inhibition response was linear over 0–360 µM, providing excellent fit (R² = 0.9991) and an ultralow detection limit of 0.042 µM (Fig. 3 B). In parallel, fluorometric readout afforded even higher analytical sensitivity, where vitamin C quenched the fluorescence signal generated during the H₂O₂-driven oxidation of the fluorogenic reporter (Fig. 3 C). The strong agreement between the chromogenic inhibition trend and the fluorescence quenching behavior supports a shared redox/ROS-mediated mechanism and underpins the reliability of the dual-mode sensing strategy. In the fluorometric configuration, the sensor exhibited a linear response from 0 to 360 µM with a detection limit of 0.003 µM, corresponding to an approximately 14-fold improvement in sensitivity relative to the colorimetric mode (Fig. 3 D). Both readouts showed good repeatability, with RSD values below 5% (n = 3), confirming acceptable precision for routine quantification. Importantly, benchmarking against previously reported approaches ( Table 1 ) highlights that the dual-mode design not only extends the practical working range but also improves analytical reliability by enabling internal cross-validation: agreement between the absorbance and fluorescence trends reduces the risk of false positives arising from matrix color, turbidity, or probe-specific artifacts. A smartphone-assisted platform was developed for vitamin C quantification by extracting RGB information from captured assay images and converting these data into numerical color metrics using Color Picker software ( Fig. S3 ). The device supports both colorimetric and fluorometric readouts, enabling dual-mode analysis within the same workflow. For the colorimetric mode, the (R + G)/B index exhibited a robust linear dependence on vitamin C concentration over 5–300 µM, providing a detection limit of 0.55 µM. In the fluorometric mode, improved sensitivity was achieved, with linearity maintained from 1.5–320 µM and a lower detection limit of 0.10 µM. Collectively, these results demonstrate that the smartphone-based configuration offers a practical and sensitive approach for dual-mode vitamin C determination, with the fluorescence channel serving as a higher-sensitivity complement to the colorimetric readout. Table 1 Comparison between proposed FeN@CNTs-based dual detection and other Fe-based systems for sensing of vitamin C. Technique Sensor Linear range (µM) LOD (µM) Reference Colorimetry Fe1.5-N-GDY 5-100 5.95 [ 48 ] CNT/FeNC 0.1–10 0.03 [ 49 ] Fe-N-C SAzyme 0.1-2 0.1 [ 50 ] Fe-N/C 0–25 0.092 [ 51 ] Fe-N-C SANs 0.5–33 0.5 [ 52 ] Fe-CDs 25–500 8.59 [ 53 ] FeN@CNTs 0-360 0.042 This work Fluorometry Fe-CDs 20.0–500 5.13 [ 53 ] FeN@CNTs 0-360 0.003 This work 3.6. Reproducibility, stability, and selectivity Across five independently fabricated batches, the FeN@CNTs nanozyme exhibited excellent batch-to-batch reproducibility, with low dispersion in analytical response (RSD = 3.60% for the colorimetric mode and 4.20% for the fluorometric mode; Fig. S4 ). These results indicate high fabrication precision and robust control over the material’s active-site performance, supporting reliable translation to routine sensing where consistent catalytic activity, long-term stability, and manufacturing repeatability are critical for quantitative readouts. Moreover, the FeN@CNTs nanozyme exhibited markedly superior operational stability compared with horseradish peroxidase (HRP) ( Fig. S5A-D ). The nanozyme retained high catalytic activity after 18 days of storage, remained resilient under extended exposure to acidic and alkaline environments, and preserved > 80% of its initial activity after 30 days of aqueous incubation ( Fig. S6 A& B ). Collectively, this stability profile highlights the intrinsic robustness of the Fe–N–C catalytic architecture and supports the platform’s suitability for long-duration sensing, where resistance to pH fluctuations and storage/handling conditions is essential for consistent quantitative performance. As illustrated in Fig. 4 , the FeN@CNTs nanozyme maintained stable colorimetric and fluorometric responses in the presence of a broad panel of potential interferents (each at 600 µM), including representative inorganic ions, common biomolecules, and polyphenols. This interference-tolerance demonstrates high analytical selectivity and minimal cross-reactivity, supporting accurate vitamin C quantification in optically and chemically complex matrices. Notably, biothiols (e.g., glutathione and cysteine) produced a pronounced effect. This behavior is mechanistically consistent with their well-established ability to quench ROS and, in metal-centered catalytic systems, to coordinate/chelate active sites, thereby suppressing ROS-mediated signal generation and/or attenuating catalytic turnover. The thiol-derived interference can be effectively mitigated by introducing a thiol-blocking maleimide reagent (commonly N-ethylmaleimide, NEM), which rapidly and covalently consumes free –SH groups via Michael-type addition, restoring assay performance by preventing thiol-driven ROS scavenging and site poisoning [ 17 , 54 ]. 3.7. Nanozyme applications To evaluate practical applicability, the FeN@CNTs nanozyme was validated in real sample matrices using dual readouts. Spiked-recovery experiments yielded recoveries of 94.5–106.9% for the colorimetric assay and 96.2–107.7% for the fluorometric assay, demonstrating accurate quantification across the tested samples ( Tables 2 and 3 ). The method also exhibited excellent precision, with RSD values below 4.28% for both detection modes, confirming strong repeatability and reproducibility. Importantly, the analytical results showed no statistically significant differences from those obtained by the reference HPLC method [ 55 ], further supporting the robustness and reliability of the proposed platform for routine analysis in diverse real-world samples. Table 2 Vitamin C recovery from different real samples using colorimetric-based mode (n = 3). Sample Added Colorimetric-mode Reference method [ 55 ] t-calculated Found Recovery (%) RSD % Found Recovery (%) RSD % Tablets (160 mg/tablet) 0.0 3.0 6.0 10.0 143.87 146.97 150.06 153.78 ----- 103.3 103.2 99.1 3.43 2.76 2.98 3.76 138.76 141.67 144.37 148.18 ----- 97.0 93.5 94.2 3.74 3.50 4.18 4.15 2.783 2.108 3.871 3.982 Tomato juice 0.0 3.0 6.0 10.0 18.67 21.87 24.78 29.01 ----- 106.7 101.8 103.4 3.13 3.76 4.10 2.87 19.76 23.01 25.87 29.45 ----- 108.3 101.8 96.9 2.74 4.484.29 5.15 3.928 4.013 3.398 4.082 Orange juice 0.0 3.0 6.0 10.0 36.48 39.42 42.48 47.17 ----- 98.0 100.0 106.9 3.54 2.98 2.76 3.47 31.89 34.86 38.26 42.18 ----- 99.0 106.1 102.9 3.10 3.29 4.92 5.37 2.873 3.011 4.178 4.180 Urine 0.0 3.0 6.0 10.0 4.78 7.92 10.87 14.23 ----- 104.7 101.5 94.5 2.78 4.01 3.67 3.39 5.32 8.67 11.87 14.89 ----- 111.7 109.2 95.6 4.98 5.01 4.28 3.98 4.019 3.276 3.721 4.119 t-tabulated at confidence level 95 % and n= 3 is 4.303. Table 3 Vitamin C recovery from different real samples using fluorometric-based mode (n = 3). Sample Added Colorimetric-mode Reference method [ 55 ] t-calculated Found Recovery (%) RSD % Found Recovery (%) RSD % Tablets (160 mg/tablet) 0.0 3.0 6.0 10.0 148.23 151.28 154.48 158.43 ----- 101.7 104.2 102.5 4.28 3.28 3.98 4.13 145.91 148.84 152.01 155.98 ----- 97.7 101.7 100.7 4.29 3.87 4.34 4.78 3.232 3.817 2.763 2.872 Tomato juice 0.0 3.0 6.0 10.0 21.32 24.47 27.78 32.01 ----- 105.0 107.7 106.9 2.87 3.28 3.77 3.98 25.83 28.76 31.45 36.02 ----- 97.7 93.7 101.9 3.76 3.984.20 3.87 2.781 3.782 2.863 3.781 Orange juice 0.0 3.0 6.0 10.0 32.89 36.11 38.86 43.19 ----- 107.3 99.5 103.0 2.87 3.10 3.78 3.76 33.65 36.89 40.02 42.99 ----- 108.0 106.2 93.4 2.78 3.82 4.11 5.56 3.271 3.311 4.078 3.280 Urine 0.0 3.0 6.0 10.0 5.12 8.30 10.89 15.11 ----- 106.0 96.2 99.9 2.78 4.01 3.67 3.39 5.54 8.63 11.78 14.98 ----- 10.3.0 104.0 94.4 3.72 4.81 5.08 4.28 4.109 3.331 3.883 4.439 t-tabulated at confidence level 95 % and n= 3 is 4.303. 4. Conclusions In summary, we have successfully developed a dual-mode colorimetric and fluorometric sensing platform for highly sensitive and selective detection of vitamin C, enabled by the robust catalytic performance of Fe and N co-doped carbon nanotubes (FeN@CNTs). The single-atom Fe–Nₓ active sites within a hierarchically porous carbon framework endow the system with exceptional peroxidase-mimicking activity, enabling efficient ROS generation and catalytic turnover under mild conditions. Both detection modes—absorbance and fluorescence—demonstrated wide linear ranges, ultralow detection limits (0.042 µM and 0.003 µM, respectively), and excellent reproducibility across multiple batches. The smartphone-assisted readout further underscores the potential for portable, on-site applications. Importantly, the platform exhibited high operational stability and strong anti-interference capability across diverse analytes and real-world samples, including fruit juices, pharmaceuticals, and urine, with recoveries closely matching HPLC benchmarks. This work not only establishes FeN@CNTs as a powerful nanozyme-based probe for vitamin C quantification but also highlights the broader utility of single-atom catalyst architectures in next-generation biosensing technologies. Future studies will aim to expand this strategy to multiplexed analyte detection and explore surface functionalization routes for enhancing molecular selectivity. Declarations Competing interests The authors declare no competing interests. Data availability Data will be made available on request. Acknowledgment This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2601). References A.M. Wu, H. Ding, W. Zhang, H.B. 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Ali","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"Al-Montaser","middleName":"Bellah H.","lastName":"Ali","suffix":""},{"id":610470751,"identity":"9740ffeb-f846-4fef-9011-6f63615dea60","order_by":5,"name":"Mohamed El-Wekil‬‏","email":"data:image/png;base64,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","orcid":"","institution":"Assiut University","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"El-Wekil‬‏","suffix":""}],"badges":[],"createdAt":"2026-02-25 15:08:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8969133/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8969133/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105368161,"identity":"74c20dc9-3e81-4fe3-9c2b-8b7fe0eb8d1f","added_by":"auto","created_at":"2026-03-25 08:57:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":502599,"visible":true,"origin":"","legend":"\u003cp\u003e(A) SEM image of PAN nanofibers; (B) SEM image of Fe–PAN@polypyrrole nanofibers; (C) SEM image of FeN@CNTs; (D) TEM image of Fe–PAN@polypyrrole nanofibers; (E) TEM image of FeN@CNTs; (F-H) Elemental mapping of C, N, and Fe, respectively; (I) XRD pattern of FeN@CNTs; (J) Raman spectra of N@CNTs and FeN@CNTs; (K) XPS survey of FeN@CNTs; (L-N) High resolution spectra of C 1s, N 1s, and Fe 2p, respectively; (O) XAS of Fe foil and FeN@CNTs; (P) Nitrogen adsorption-desorption isotherm of FeN@CNTs.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/efe17bbde8c90787bc0569c2.png"},{"id":105368153,"identity":"58498289-158e-432b-87b8-37f8b95941c7","added_by":"auto","created_at":"2026-03-25 08:57:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":218777,"visible":true,"origin":"","legend":"\u003cp\u003eEvaluation of the peroxidase-mimetic activity of FeN@CNTs: (A) UV–vis absorption spectra of different reaction systems: TMB+H₂O₂, FeN@CNTs, FeN@CNTs+TMB, and FeN@CNTs+TMB + H₂O₂. (B) Comparison of catalytic performance via UV–vis spectra: TMB+H₂O₂, N@CNTs+TMB+H₂O₂, and FeN@CNTs+TMB+H₂O₂. (C) Time-dependent kinetic profile of TMB oxidation catalyzed by FeN@CNTs. (D) Fluorescence spectra of different systems: AR+H₂O₂, FeN@CNTs, FeN@CNTs+ AR, and FeN@CNTs+ AR + H₂O₂. (E) Comparative fluorescence spectra of AR+H₂O₂, N@CNTs +AR+ H₂O₂, and FeN@CNTs+ AR+H₂O₂. (F) Time-dependent kinetic profile of AR oxidation catalyzed by FeN@CNTs.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/7dbc7d71a5db3b07f71a014d.png"},{"id":105368118,"identity":"faffd3df-e73e-4e46-91d5-d3e2a4825c4f","added_by":"auto","created_at":"2026-03-25 08:57:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":188090,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Absorbance changes in the colorimetric assay for vitamin C (0–360 μM); (B) Corresponding ΔA vs. vitamin C concentration plot; (C) Fluorescence spectra upon vitamin C addition (0–360 μM); (D) Plot of F\u003csup\u003e₀\u003c/sup\u003e/F vs. vitamin C concentration. Results shown are averages of triplicate assays.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/da7f7d3af09de1ef074f03b0.png"},{"id":105368155,"identity":"0dd1328a-7372-4c20-b1c3-6656b53dc278","added_by":"auto","created_at":"2026-03-25 08:57:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":257507,"visible":true,"origin":"","legend":"\u003cp\u003eSelectivity of FeN@CNTs nanozyme towards detection of vitamin C, metal ions, biomolecules, and polyphenols using (A, B) colorimetric and (C, D) fluorometric assays. All measurements were performed in triplicate.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/08252af4222261f7d9ead6b9.png"},{"id":105374358,"identity":"7dbf033c-96f5-4ef6-8b90-1c8ccbaeaaf2","added_by":"auto","created_at":"2026-03-25 09:58:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2127749,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/e2b927e5-93ab-4599-9028-40defbc20a85.pdf"},{"id":105368117,"identity":"2feb6255-8eb9-4080-ae53-9003a2aa0de3","added_by":"auto","created_at":"2026-03-25 08:57:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3440497,"visible":true,"origin":"","legend":"","description":"","filename":"ElectronicSupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/789a7607790f43f77d8bb9fc.docx"},{"id":105368128,"identity":"765c3f0f-8ee5-4748-a7cd-321d70116d05","added_by":"auto","created_at":"2026-03-25 08:57:41","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":988355,"visible":true,"origin":"","legend":"","description":"","filename":"Scheme1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8969133/v1/9b42ebea7eb11273ffa6ebe5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electrospun FeN@CNT single-atom nanozyme for triple-mode ROS-mediated colorimetric and fluorometric detection of vitamin C","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eVitamin C is an essential water-soluble antioxidant that exhibits strong reducing capability and plays a pivotal role in maintaining redox homeostasis and supporting fundamental metabolic processes in the human body [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Insufficient levels of vitamin C impair collagen biosynthesis and compromise cellular structural integrity, which can precipitate pathological conditions including immune dysfunction, scurvy, cardiovascular disorders, and anemia [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although most mammals are capable of synthesizing vitamin C endogenously, humans lack this ability and must therefore rely on dietary intake [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], which has driven its extensive utilization in the food and pharmaceutical industries. Beyond its nutritional significance, vitamin C exhibits strong free-radical scavenging activity and tyrosinase inhibition, underpinning its widespread application in cosmetic formulations aimed at antioxidative protection and skin-whitening effects [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nevertheless, excessive intake of vitamin C may elicit adverse health effects, including nephrolithiasis, diarrhea, and gastrointestinal discomfort [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consequently, the development of simple, accurate, and reliable analytical methods for vitamin C determination is of considerable importance for food safety, quality control, and related application domains.\u003c/p\u003e \u003cp\u003eTo date, numerous analytical methods have been used to quantify vitamin C, such as HPLC [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], capillary electrophoresis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], LC/MS [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and electrochemical voltammetry [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although chromatographic techniques provide excellent sensitivity and precision, they typically involve expensive operation, lengthy sample preparation and analysis, and sophisticated instrumentation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Electrochemical methods, in contrast, provide a cost-effective and sensitive alternative; however, they are frequently hindered by challenges such as electrode fouling, limited selectivity, and interference from coexisting species [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. By comparison, colorimetric and fluorometric methods offer several advantages, including low cost, ease of visualization, good accuracy, and simple operation, making them particularly suitable for rapid and on-site analysis.\u003c/p\u003e \u003cp\u003eArtificial nanomaterial-based enzymes, commonly referred to as nanozymes, have emerged as a versatile and promising alternative to natural enzymes due to their tunable structures, high stability, and cost-effectiveness [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. By emulating the catalytic mechanisms of natural enzymes, nanozymes can exhibit significant catalytic activity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Over the past decade, substantial research efforts have broadened the diversity of nanozymes, facilitating their applications in catalysis, biomedical therapy, environmental remediation, tissue engineering, and biosensing [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Nonetheless, the relatively modest catalytic efficiency of many nanozymes continues to limit their full potential and widespread practical deployment.\u003c/p\u003e \u003cp\u003eStrategies to enhance nanozyme activity typically focus on tuning particle size and morphology, engineering specific crystal facets, and modulating surface charge and composition [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, many nanozymes continue to display limited catalytic performance, primarily due to unevenly distributed active sites and suboptimal atomic utilization [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This challenge has spurred interest in designing nanozymes with highly abundant, well-defined active centers. In this context, single-atom catalysts (SACs), first reported in 2011, have attracted considerable attention owing to their exceptional catalytic efficiency, maximized atomic utilization, and cost-effective performance in catalysis and energy-related applications [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Single-atom catalysts (SACs), created by immobilizing individual metal atoms on solid supports, combine distinctive geometric and electronic characteristics with atomically defined active sites and nearly complete metal-atom utilization [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Notably, nitrogen-doped carbon frameworks containing M\u0026ndash;N\u0026ndash;C motifs can host atomically dispersed metals as M\u0026ndash;Nx sites, which closely resemble the active centers found in natural enzymes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This approach has led to the emergence of single-atom nanozymes (SAzymes) with outstanding catalytic activity. In addition, the uniformity and clear definition of SAzyme active sites make it possible to systematically probe structure\u0026ndash;activity relationships and reaction pathways, offering important guidance for rational catalyst design [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Various strategies have been developed for the synthesis of SAzymes, including atomic layer deposition, impregnation, and coprecipitation, all of which rely on the precise arrangement of environmental atoms and defect sites in supports such as metal\u0026ndash;organic frameworks (MOFs) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and nitrogen-doped carbon materials [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Despite these advancements, these methods often struggle to fully prevent metal atom aggregation during high-temperature pyrolysis, frequently necessitating additional acid-etching treatments. Furthermore, the formation of single-atom sites is typically random, resulting in limited reproducibility and challenges for large-scale, uniform production [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, iron- and nitrogen-co-doped carbon nanotube catalysts (Fe,N@CNTs) were fabricated via electrospinning and hydrothermal treatment followed by carbonization. The synthesis was designed to maximize the utilization of single-atom Fe sites, thereby enhancing enzyme-mimicking catalytic activity. Initially, a tubular polypyrrole structure was constructed, which subsequently enables the \u003cem\u003ein situ\u003c/em\u003e formation of highly active Fe\u0026ndash;N\u0026ndash;C sites within the carbon matrix (\u003cb\u003eScheme 1\u003c/b\u003e). The resulting Fe, N@CNTs exhibit remarkable peroxidase-like activity, attributed to the synergistic effects of well-defined Fe\u0026ndash;N\u0026ndash;C active sites and the tubular architecture, which facilitate efficient electron transfer and mass transport. Furthermore, these catalysts are employed as a dual-mode platform for both colorimetric and fluorometric detection of vitamin C, demonstrating their potential for sensitive and reliable analytical applications.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Materials and reagents\u003c/h2\u003e\n \u003cp\u003eReagents and chemicals were sourced as follows. From Sigma-Aldrich (Germany), we obtained vitamin C (99.4%), glutathione (GSH, 98.7%), 3,3\u0026prime;,5,5\u0026prime;-tetramethylbenzidine (TMB), pyrrole (98.8%), 5,5-dimethyl-1-pyrroline-N-oxide (DMPO), 1,4-benzoquinone (PBQ; 97.9%), isopropyl alcohol (IPA, 99.5%), thiourea (99.7%), Amplex Red (AR, 98.7%), terephthalic acid (TA, 99.0%), L-histidine (L-His, 98.7%), thiourea (ThU, 99.8%), furfuryl alcohol (FA, AR), glucose (99.5%), uric acid (97.0%),, dopamine hydrochloride (97.4%), tryptophan (98.0%), cholesterol (98.9%), alanine (97.5%), cysteine (98.7%), Ferulic acid (98.9%), luteoin (98.0%), caffeic acid (99.4%), phenylalanine (98.4%), Gallic acid (99.8%), bovine serum albumin (BSA, 98.7%), and methionine (98.5%), and Polyacrylonitrile (PAN, Mw\u0026thinsp;=\u0026thinsp;80,000) fibrils were purchased from Sigma-Aldrich (Germany). Additional reagents\u0026mdash;hydrogen peroxide (H₂O₂, 30.0%), dimethylformamide (DMF), ammonium persulfate, acetic acid (CH₃COOH), boric acid (H₃BO₃), phosphoric acid (H₃PO₄), and ferric chloride hexahydrate (FeCl3\u0026bull;6H₂O)\u0026mdash;were supplied by Merck (Germany). Deionized water was used in all experiments.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Instruments\u003c/h2\u003e\n \u003cp\u003eComprehensive specifications of the instruments used, including calibration and operating parameters, are provided in the Supporting Information.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Preparation of FeN@CNTs\u003c/h2\u003e\n \u003cp\u003ePoly(pyrrole) nanofibers were prepared by electrospinning a 10.5 wt % PAN solution in DMF maintained at 100\u0026deg;C. Electrospinning was performed at an applied voltage of 22 kV with a 25 cm tip-to-collector distance. The resulting fibrous membrane (100 mg) was dispersed in deionized water (60 mL), followed by addition of pyrrole (200 \u0026micro;L). Oxidative polymerization was initiated by FeCl₃\u0026bull;6H₂O solution (5 mL, 50 mg mL⁻\u0026sup1;). The product was thoroughly washed and dried; a 30 mL portion of the dispersion was then subjected to hydrothermal treatment at 220\u0026deg;C to remove residual PAN, yielding Fe\u0026ndash;poly(pyrrole) nanotubes. Finally, the nanotubes were carbonized at 800\u0026deg;C to obtain FeN@CNTs (\u003cstrong\u003eScheme S1\u003c/strong\u003e). As a control, N@CNTs were synthesized using an identical procedure, with ammonium persulfate replacing FeCl₃\u0026middot;6H₂O as the oxidant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Steady-state kinetics\u003c/h2\u003e\n \u003cp\u003eSteady-state kinetics were used to quantify the nanozyme\u0026rsquo;s peroxidase-mimicking activity with TMB as the colorimetric substrate. Reactions were performed at constant H₂O₂ (25 mM) and TMB (0.4 mM), and the reaction kinetics were followed by recording the absorbance as a function of time. Initial rates (v) were extracted from the linear region of the absorbance\u0026ndash;time traces and fitted to the Michaelis\u0026ndash;Menten equation to obtain kinetic parameters. Apparent Km and V\u003csub\u003emax\u003c/sub\u003e were also derived from the Lineweaver\u0026ndash;Burk plot using:\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n \u003cp\u003eWhere V is the initial velocity, [S] is the substrate concentration, Km is the Michaelis constant, and V\u003csub\u003emax\u003c/sub\u003e is the maximum rate of the reaction.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Detection steps\u003c/h2\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.5.1. Colorimetric method\u003c/h2\u003e\n \u003cp\u003eVitamin C standards at different concentrations were incubated in BR buffer (pH 3.8). The reaction mixture was assembled by stepwise addition of H₂O₂ (200 \u0026micro;L, 2.8 mM), TMB (300 \u0026micro;L, 2.2 mM), and FeN@CNTs nanozyme dispersion (100 \u0026micro;L, 90 \u0026micro;g mL⁻\u0026sup1;), followed by dilution to a total volume of 1.0 mL with BR buffer (pH 3.8). The mixture was incubated at room temperature for 6 min, and the absorbance of oxidized TMB was measured at 650 nm.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.5.2. Fluorometric method\u003c/h2\u003e\n \u003cp\u003eFor fluorescence detection of vitamin C, reactions were prepared in BR buffer (pH 3.8) by sequentially mixing 200 \u0026micro;L of H₂O₂ (2.8 mM), 200 \u0026micro;L of Amplex Red (AR, 1.8 mM), and 100 \u0026micro;L of FeN@CNTs (90 \u0026micro;g mL⁻\u0026sup1;), followed by dilution to 1.0 mL with BR buffer. The mixture was incubated for 5 min at room temperature, and fluorescence was measured at 590 nm.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.5.3. Smartphone-based detection\u003c/h2\u003e\n \u003cp\u003eTo assess portability, both TMB and Amplex Red assays were adapted for smartphone-based detection. After the reaction, mixtures were transferred to a transparent 96-well plate. Images were captured using a smartphone camera (Infinix Pro 10) under consistent lighting, with the phone fixed\u0026thinsp;~\u0026thinsp;15 cm above the sample. For colorimetric assays, blue-channel intensity (650 nm) was extracted using a Color Picker app. For fluorescence assays, a portable UV flashlight (365 nm) was used for excitation, and red-channel intensity (590 nm) was analyzed. A black enclosure was used to minimize ambient light interference. Extracted color intensities were plotted against vitamin C concentrations to generate standard calibration curves (\u003cstrong\u003eScheme S2\u003c/strong\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6. Real samples analysis\u003c/h2\u003e\n \u003cp\u003eA tablet powder sample (0.5 mg) was dissolved in 15 mL of ultrapure water. For fruit matrices (orange or tomato), 1.5 g of sample was homogenized with 2.5 mL of ultrapure water, followed by centrifugation at 10,000 rpm for 15 min; the resulting supernatant was then collected. Tablet solutions, fruit supernatants, and beverage samples were passed through a 0.45 \u0026micro;m filter and diluted with BR buffer (pH 3.8) prior to spiked recovery experiments. Vitamin C levels were determined using the FeN@CNTs nanozyme assay under the same conditions applied for the calibration standards. All analyses were conducted in triplicate, and results are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Urine samples were diluted 10-fold with BR buffer (pH 3.8), spiked with vitamin C, and evaluated using the identical sensing protocol.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results and discussions","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Characterization\u003c/h2\u003e\n \u003cp\u003eThe fabrication of FeN@CNTs is outlined in \u003cstrong\u003eScheme 1\u003c/strong\u003e. Briefly, PAN nanofibers (\u0026asymp;\u0026thinsp;180.79 nm average diameter, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) are first produced by electrospinning to serve as a uniform, high-surface-area scaffold that enables conformal coating and preserves 1D morphology during subsequent processing. Pyrrole is then adsorbed onto the PAN surface, followed by the introduction of Fe\u0026sup3;⁺, which simultaneously acts as an oxidizing initiator for \u003cem\u003ein situ\u003c/em\u003e polymerization and as a metal source to promote coordination with nitrogen functionalities. This step yields a Fe-containing poly(pyrrole) sheath anchored on the PAN fibers, creating precursor architecture designed to maximize the density and accessibility of Fe\u0026ndash;Nₓ motifs after thermal conversion.\u003c/p\u003e\n \u003cp\u003eAs evidenced by SEM analysis, the Fe\u0026ndash;PAN@polypyrrole nanofibers exhibit a significantly increased average diameter (~\u0026thinsp;205.73 nm) compared with pristine PAN fibers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB \u003cstrong\u003eand D\u003c/strong\u003e), indicating the successful deposition of the Fe-containing polypyrrole layer. Subsequent hydrothermal treatment effectively removes the PAN core, resulting in dimensionally uniform FeN@CNTs. The hollow tubular morphology and structural uniformity of the resulting materials are clearly confirmed by both SEM and TEM observations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC \u003cstrong\u003eand E\u003c/strong\u003e). Elemental mapping of the FeN@CNTs confirms the homogeneous distribution of C, N, and Fe throughout the nanotube framework (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF\u0026ndash;H), supporting successful incorporation of Fe within the nitrogen-containing carbon matrix. Quantitative inductively coupled plasma analysis further determines a Fe content of 1.08 wt%, which falls within the typical loading range reported for Fe-based single-atom catalysts and related Fe\u0026ndash;N\u0026ndash;C architectures [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe XRD profile of FeN@CNTs displays a single broad halo centered within 2\u0026theta;\u0026thinsp;\u0026asymp;\u0026thinsp;20\u0026ndash;45\u0026deg; and lacks sharp Bragg reflections (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI), consistent with a predominantly turbostratic/amorphous carbon framework and the absence of detectable crystalline Fe-containing phases. While XRD cannot directly prove atomic dispersion, the featureless pattern\u0026mdash;together with the lack of Fe/FeOx signatures\u0026mdash;supports that iron is present below the XRD detection limit and/or incorporated as highly dispersed species. Raman spectra show the characteristic D band (~\u0026thinsp;1373 cm⁻\u0026sup1;) and G band (~\u0026thinsp;1584 cm⁻\u0026sup1;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ), confirming the coexistence of defect-rich and graphitized carbon domains. Notably, the rise in the I\u003csub\u003eD\u003c/sub\u003e/I\u003csub\u003eG\u003c/sub\u003e ratio upon Fe incorporation indicates an increased density of structural defects/edge sites, which can promote catalytic turnover by (i) creating additional adsorption/activation sites and (ii) providing coordination/anchoring environments (e.g., Fe\u0026ndash;Nx motifs) that stabilize isolated Fe centers within the carbon lattice [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe chemical states of the constituent elements and the local Fe\u0026ndash;N coordination in FeN@CNTs were interrogated using complementary X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) analyses. The XPS survey spectrum shows dominant signals from C, N, and O, while the Fe signal remains weak, as expected for the low Fe loading (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK). Deconvolution of the high-resolution C 1s spectrum (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eL) yields components at 284.8 eV (C\u0026thinsp;=\u0026thinsp;C), 285.9 eV (C\u0026ndash;N), and 287.4 eV (C\u0026ndash;O), confirming the formation of a heteroatom-enriched carbon framework with substantial N incorporation [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The N 1s spectrum (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eM) can be fitted with peaks centered at 396.2, 399.6, 400.7, and 401.2 eV, assigned to pyridinic N, pyrrolic N, graphitic N, and oxidized N, respectively [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Importantly, pyridinic and pyrrolic nitrogens are widely recognized as effective coordination/anchoring sites for isolated Fe species, facilitating the formation of Fe\u0026ndash;Nx motifs and suppressing Fe aggregation, whereas graphitic N\u0026mdash;embedded within the carbon basal plane\u0026mdash;modulates charge density and electronic conductivity, thereby influencing catalytic kinetics. In the Fe 2p region (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eN), the fitted peaks at 709.2, 714.5, and 721.3 eV correspond to Fe\u0026sup2;⁺ 2p\u003csub\u003e3/2\u003c/sub\u003e, Fe\u0026sup3;⁺ 2p\u003csub\u003e3/2\u003c/sub\u003e, and Fe\u0026sup2;⁺ 2p\u003csub\u003e1/2\u003c/sub\u003e, respectively, indicating the coexistence of mixed-valence Fe species stabilized by the N-doped carbon matrix [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTo elucidate the local coordination environment of Fe in FeN@CNTs, XAS was employed. As shown in Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eO, the absorption features are consistent with Fe existing in a positively charged state, which is commonly associated with coordination to electronegative N ligands in Fe\u0026ndash;N\u0026ndash;C architectures. In the Fourier-transformed EXAFS profile, FeN@CNTs exhibit a dominant first-shell peak at ~\u0026thinsp;1.47 \u0026Aring;, assignable to Fe\u0026ndash;N scattering, whereas metallic Fe foil displays a characteristic Fe\u0026ndash;Fe contribution at ~\u0026thinsp;2.25 \u0026Aring;. Notably, the absence (or pronounced suppression) of Fe\u0026ndash;Fe coordination in FeN@CNTs relative to Fe foil supports that Fe is present predominantly as isolated, single-site species rather than aggregated nanoparticles. Collectively, these XAS results substantiate the formation of atomically dispersed Fe\u0026ndash;Nx moieties embedded within the N-doped carbon nanotube framework. Such single-site anchoring can maximize the accessibility of Fe centers and stabilize the active configuration under reaction conditions, providing a plausible structural basis for the enhanced catalytic performance observed for FeN@CNTs. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eNitrogen adsorption\u0026ndash;desorption measurements of FeN@CNTs typically show a type-IV isotherm with an evident hysteresis loop, indicating a mesoporous architecture arising from the hollow nanotube channels and inter-tube voids. A noticeable uptake at low relative pressure (P/P\u003csup\u003e0\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1) suggests the presence of micropores introduced during carbonization/activation of the poly(pyrrole) framework. Overall, the resulting high specific surface area \u003cstrong\u003e(~\u003c/strong\u003e\u0026thinsp;389.78 m\u0026sup2; g⁻\u003csup\u003e1\u003c/sup\u003e\u003cstrong\u003e)\u003c/strong\u003e and hierarchical micro/mesoporosity provide abundant exposed/accessible Fe\u0026ndash;Nx sites and facilitate rapid mass transport, which is favorable for catalytic performance (Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eP).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Peroxidase-mimic activity\u003c/h2\u003e\n \u003cp\u003eTMB is widely used as a chromogenic probe for benchmarking the peroxidase-like activity of nanozymes. Under acidic conditions, peroxidase-mimicking catalysts activate H₂O₂ to generate reactive oxygen species (ROS), primarily \u0026bull;OH andO₂\u0026bull;⁻, which subsequently oxidize colorless TMB to its blue charge-transfer product. The formation of oxTMB yields a distinct visible absorption band (typically centered around ~\u0026thinsp;652 nm), allowing the catalytic reaction rate and overall activity to be quantified spectrophotometrically with high sensitivity. Upon H₂O₂ addition, a sharp rise in absorbance was observed, confirming the catalyst\u0026rsquo;s peroxidase-like behavior (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Notably, FeN@CNTs outperformed control materials, reflecting superior catalytic efficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). This performance arises from the combined effect of a highly porous carbon framework, which enhances reactant transport, and evenly distributed Fe\u0026ndash;Nₓ sites, which catalyze H₂O₂ breakdown and ROS generation. These structural and electronic features together contribute to the exceptional activity of FeN@CNTs. Time-dependent kinetic measurements demonstrate that FeN@CNTs efficiently catalyze the oxidation of TMB, as reflected by the continuous increase in the characteristic absorbance at ~\u0026thinsp;650 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Relative to the corresponding control systems, FeN@CNTs produce a markedly steeper initial slope, indicating a substantially higher apparent catalytic rate. Notably, the absorbance\u0026ndash;time profile remains linear during the first 300 s, suggesting that the reaction proceeds under kinetic control within this window. Accordingly, a fixed incubation time of 300 s was adopted as the standard reaction interval for subsequent activity comparisons and sensing measurements to ensure consistent quantification under the initial-rate regime.\u003c/p\u003e\n \u003cp\u003eMichaelis\u0026ndash;Menten kinetics were employed to quantify the intrinsic catalytic behavior of FeN@CNTs toward both H₂O₂ and TMB, and the corresponding Lineweaver\u0026ndash;Burk plots are provided in \u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/strong\u003e. The extracted parameters indicate a strong substrate affinity, with Km values of 1.87 mM for H₂O₂ and 0.176 mM for TMB, together with high maximal velocities (V\u003csub\u003emax\u003c/sub\u003e=20.17\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e and 18.02\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e M\u0026middot;s⁻\u0026sup1; for H₂O₂ and TMB, respectively). Collectively, these kinetic metrics verify efficient peroxidase-like catalysis and compare favorably with representative Fe-based nanozymes reported in the literature (\u003cstrong\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/strong\u003e). Mechanistically, the performance can be rationalized by the synergistic architecture: atomically dispersed Fe\u0026ndash;Nx motifs provide accessible redox-active centers for H₂O₂ activation and electron transfer, whereas the conductive, porous CNT network facilitates reactant diffusion and enhances exposure of catalytic sites. This combination of high-affinity kinetics and structural accessibility supports the use of FeN@CNTs as a robust platform for catalytic assays and (bio)sensing readouts.\u003c/p\u003e\n \u003cp\u003eTo further corroborate the peroxidase-like activity of FeN@CNTs using an orthogonal readout, we employed a fluorometric assay based on Amplex Red (AR). In the presence of H₂O₂, FeN@CNTs catalyze the oxidation of AR to resorufin, generating a strong emission centered at ~\u0026thinsp;590 nm upon excitation at 542 nm. As depicted in Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, the FeN@CNTs/H₂O₂/AR system produces a substantially higher fluorescence intensity as the corresponding control groups, evidencing more efficient H₂O₂ activation and substrate turnover. The quantitative comparison in Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE confirms this enhancement and shows strong consistency with the activity trends obtained from the TMB colorimetric assay, indicating that the observed catalytic behavior is robust across independent detection modalities. Kinetic traces (Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) further demonstrate rapid AR oxidation catalyzed by FeN@CNTs, as reflected by the continuous increase in fluorescence at ~\u0026thinsp;590 nm over time. The markedly steeper initial slope relative to controls highlights a higher apparent reaction rate. Importantly, the fluorescence response remains linear within the first 300 s, supporting that the reaction proceeds under initial-rate (kinetically controlled) conditions before substantial substrate depletion or product accumulation occurs. Therefore, a standardized incubation time of 300 s was selected for subsequent catalytic comparisons and sensing experiments to ensure reproducible quantification within the linear regime.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Detection mechanism\u003c/h2\u003e\n \u003cp\u003eEDTA was introduced as a chelating inhibitor to interrogate the nature of the catalytically active sites in FeN@CNTs. Upon EDTA addition, the catalytic response decreased sharply (\u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA\u003c/strong\u003e), evidenced by a pronounced attenuation of the 650 nm absorbance. Given EDTA\u0026rsquo;s strong affinity for iron ions, this suppression is consistent with coordination of EDTA to the Fe centers, which competitively blocks substrate access and diminishes turnover. Collectively, the inhibition outcome supports that Fe-based sites are directly responsible for the observed peroxidase-like activity rather than the carbon framework alone. The peroxidase-mimicking performance of FeN@CNTs is attributed to the concerted effects of atomically coordinated Fe\u0026ndash;Nₓ sites, abundant accessible surface area, and hierarchical pore channels that collectively accelerate reactant adsorption and mass transport. To identify the reactive oxygen species (ROS) involved, scavenger tests were conducted using thiourea (ThU, \u0026bull;OH quencher), p-benzoquinone (PBQ, \u0026bull;O₂⁻ quencher), and furfuryl alcohol/L-histidine (FA/L-His, \u0026sup1;O₂ quenchers). In all cases, increasing scavenger concentration progressively suppressed the TMB oxidation signal at 650 nm (\u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB\u003c/strong\u003e), confirming ROS participation in the catalytic pathway. Notably, the strongest inhibition was observed for ThU and PBQ, indicating that \u0026bull;OH and \u0026bull;O₂⁻ dominate the reaction mechanism, whereas \u0026sup1;O₂ plays a comparatively minor role. Electron spin resonance (ESR) measurements with DMPO as a spin-trapping agent provided direct evidence for radical formation during catalysis. As shown in \u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC\u003c/strong\u003e, the characteristic quartet pattern (1:2:2:1) corresponding to the DMPO\u0026ndash;\u0026bull;OH adduct and the diagnostic DMPO\u0026ndash;\u0026bull;O₂⁻ adduct signal were clearly observed, confirming that FeN@CNTs catalytically generate both \u0026bull;OH and \u0026bull;O₂⁻ species under the reaction conditions. These ESR results corroborate the scavenger experiments and support a radical-driven oxidation pathway. The FeN@CNTs/TA/H₂O₂ system produced a pronounced fluorescence enhancement, consistent with \u0026bull;OH-mediated oxidation of TA to the highly fluorescent 2-hydroxy TA, thereby confirming \u0026bull;OH formation during catalysis (\u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD)\u003c/strong\u003e. Complementary inhibition experiments further supported superoxide participation: introduction of superoxide dismutase (SOD) substantially suppressed the catalytic response, indicating that \u0026bull;O₂⁻ radicals are also generated and contribute to the overall peroxidase-like oxidation process (\u003cstrong\u003eFig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE)\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eVitamin C suppresses peroxidase-mimicking nanozyme reactions through multiple, often concurrent pathways: (i) it consumes H₂O₂ via direct redox reaction, lowering the effective oxidant concentration; (ii) it scavenges ROS and/or reduces high-valent metal\u0026ndash;oxo intermediates, thereby interrupting the catalytic cycle; (iii) it chemically reduces the oxidized chromogenic/fluorogenic reporter (e.g., oxTMB or resorufin) back to its reduced form, diminishing the analytical signal; and, in some systems, (iv) it adsorbs to or coordinates with catalytic centers, partially blocking active sites and modulating surface redox properties.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Optimization of conditions\u003c/h2\u003e\n \u003cp\u003eCatalytic assay parameters were systematically optimized by independently tuning pH, temperature, incubation time, FeN@CNTs loading, and substrate concentration to maximize signal intensity while preserving kinetic linearity. The nanozyme exhibited its highest apparent peroxidase-like activity at pH 3.8 in BR buffer, a condition that favors H₂O₂ activation and accelerates electron-transfer reactions on Fe\u0026ndash;Nₓ sites (\u003cstrong\u003eFig. S2A\u003c/strong\u003e). This acidic optimum is also advantageous analytically because it suppresses spontaneous background oxidation of the reporter in control systems, thereby improving the signal-to-noise ratio and the robustness of subsequent quantitative measurements [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eFeN@CNTs retained more than 78% of its maximal catalytic activity across 20\u0026ndash;60\u0026deg;C, indicating good thermal tolerance and enabling reliable operation without strict temperature control (\u003cstrong\u003eFig. S2B\u003c/strong\u003e). The response increased monotonically with nanozyme dosage, consistent with a higher density of accessible Fe\u0026ndash;Nₓ active sites and greater catalytic turnover. A working concentration of 90 \u0026micro;g mL⁻\u0026sup1; was therefore selected as an optimal compromise between signal intensity, reagent consumption, and cost-effectiveness, while maintaining a clear dynamic range for quantitative measurements (\u003cstrong\u003eFig. S2C\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003eMaximal chromogenic response was obtained at 2.2 mM TMB and 2.8 mM H₂O₂, reflecting an optimal balance between oxidant availability and substrate saturation while avoiding signal loss from over-oxidation and elevated background at higher concentrations (\u003cstrong\u003eFig. S2D, E\u003c/strong\u003e). For the fluorometric pathway, the strongest emission was achieved using 2.8 mM H₂O₂ and 1.8 mM AR (\u003cstrong\u003eFig. S2F\u003c/strong\u003e), consistent with efficient ROS-driven conversion of AR to its fluorescent product under the FeN@CNTs-catalyzed conditions. Notably, the shared optimum H₂O₂ level across both readouts indicates a common oxidant-controlled step in the catalytic cycle, supporting mechanistic consistency between the colorimetric and fluorescence modes. Collectively, these optimized parameters provide a robust operating window that improves signal-to-noise, minimizes run-to-run variability, and enables reproducible dual-mode sensing performance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5. Quantitative parameters\u003c/h2\u003e\n \u003cp\u003eVitamin C markedly suppressed FeN@CNTs-catalyzed TMB oxidation by consuming reactive oxygen species and/or reducing oxidized TMB back to its colorless form, leading to a concentration-dependent decrease in absorbance at 650 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The inhibition response was linear over 0\u0026ndash;360 \u0026micro;M, providing excellent fit (R\u0026sup2; = 0.9991) and an ultralow detection limit of 0.042 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In parallel, fluorometric readout afforded even higher analytical sensitivity, where vitamin C quenched the fluorescence signal generated during the H₂O₂-driven oxidation of the fluorogenic reporter (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The strong agreement between the chromogenic inhibition trend and the fluorescence quenching behavior supports a shared redox/ROS-mediated mechanism and underpins the reliability of the dual-mode sensing strategy.\u003c/p\u003e\n \u003cp\u003eIn the fluorometric configuration, the sensor exhibited a linear response from 0 to 360 \u0026micro;M with a detection limit of 0.003 \u0026micro;M, corresponding to an approximately 14-fold improvement in sensitivity relative to the colorimetric mode (Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Both readouts showed good repeatability, with RSD values below 5% (n\u0026thinsp;=\u0026thinsp;3), confirming acceptable precision for routine quantification. Importantly, benchmarking against previously reported approaches (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e) highlights that the dual-mode design not only extends the practical working range but also improves analytical reliability by enabling internal cross-validation: agreement between the absorbance and fluorescence trends reduces the risk of false positives arising from matrix color, turbidity, or probe-specific artifacts.\u003c/p\u003e\n \u003cp\u003eA smartphone-assisted platform was developed for vitamin C quantification by extracting RGB information from captured assay images and converting these data into numerical color metrics using Color Picker software (\u003cstrong\u003eFig. S3\u003c/strong\u003e). The device supports both colorimetric and fluorometric readouts, enabling dual-mode analysis within the same workflow. For the colorimetric mode, the (R\u0026thinsp;+\u0026thinsp;G)/B index exhibited a robust linear dependence on vitamin C concentration over 5\u0026ndash;300 \u0026micro;M, providing a detection limit of 0.55 \u0026micro;M. In the fluorometric mode, improved sensitivity was achieved, with linearity maintained from 1.5\u0026ndash;320 \u0026micro;M and a lower detection limit of 0.10 \u0026micro;M. Collectively, these results demonstrate that the smartphone-based configuration offers a practical and sensitive approach for dual-mode vitamin C determination, with the fluorescence channel serving as a higher-sensitivity complement to the colorimetric readout.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Comparison between proposed FeN@CNTs-based dual detection and other Fe-based systems for sensing of vitamin C.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTechnique\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSensor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eLinear range (\u0026micro;M)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eLOD (\u0026micro;M)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eColorimetry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe1.5-N-GDY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5-100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCNT/FeNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.1\u0026ndash;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe-N-C SAzyme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe-N/C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026ndash;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe-N-C SANs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.5\u0026ndash;33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe-CDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e25\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e8.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFeN@CNTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0-360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003eThis work\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFluorometry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFe-CDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e20.0\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFeN@CNTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0-360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cstrong\u003eThis work\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6. Reproducibility, stability, and selectivity\u003c/h2\u003e\n \u003cp\u003eAcross five independently fabricated batches, the FeN@CNTs nanozyme exhibited excellent batch-to-batch reproducibility, with low dispersion in analytical response (RSD\u0026thinsp;=\u0026thinsp;3.60% for the colorimetric mode and 4.20% for the fluorometric mode; \u003cstrong\u003eFig. S4\u003c/strong\u003e). These results indicate high fabrication precision and robust control over the material\u0026rsquo;s active-site performance, supporting reliable translation to routine sensing where consistent catalytic activity, long-term stability, and manufacturing repeatability are critical for quantitative readouts.\u003c/p\u003e\n \u003cp\u003eMoreover, the FeN@CNTs nanozyme exhibited markedly superior operational stability compared with horseradish peroxidase (HRP) (\u003cstrong\u003eFig. S5A-D\u003c/strong\u003e). The nanozyme retained high catalytic activity after 18 days of storage, remained resilient under extended exposure to acidic and alkaline environments, and preserved\u0026thinsp;\u0026gt;\u0026thinsp;80% of its initial activity after 30 days of aqueous incubation (\u003cstrong\u003eFig. S6 A\u0026amp; B\u003c/strong\u003e). Collectively, this stability profile highlights the intrinsic robustness of the Fe\u0026ndash;N\u0026ndash;C catalytic architecture and supports the platform\u0026rsquo;s suitability for long-duration sensing, where resistance to pH fluctuations and storage/handling conditions is essential for consistent quantitative performance.\u003c/p\u003e\n \u003cp\u003eAs illustrated in Fig. \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the FeN@CNTs nanozyme maintained stable colorimetric and fluorometric responses in the presence of a broad panel of potential interferents (each at 600 \u0026micro;M), including representative inorganic ions, common biomolecules, and polyphenols. This interference-tolerance demonstrates high analytical selectivity and minimal cross-reactivity, supporting accurate vitamin C quantification in optically and chemically complex matrices. Notably, biothiols (e.g., glutathione and cysteine) produced a pronounced effect. This behavior is mechanistically consistent with their well-established ability to quench ROS and, in metal-centered catalytic systems, to coordinate/chelate active sites, thereby suppressing ROS-mediated signal generation and/or attenuating catalytic turnover. The thiol-derived interference can be effectively mitigated by introducing a thiol-blocking maleimide reagent (commonly N-ethylmaleimide, NEM), which rapidly and covalently consumes free \u0026ndash;SH groups via Michael-type addition, restoring assay performance by preventing thiol-driven ROS scavenging and site poisoning [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e3.7. Nanozyme applications\u003c/h2\u003e\n \u003cp\u003eTo evaluate practical applicability, the FeN@CNTs nanozyme was validated in real sample matrices using dual readouts. Spiked-recovery experiments yielded recoveries of 94.5\u0026ndash;106.9% for the colorimetric assay and 96.2\u0026ndash;107.7% for the fluorometric assay, demonstrating accurate quantification across the tested samples (\u003cstrong\u003eTables\u0026nbsp;2 and 3\u003c/strong\u003e). The method also exhibited excellent precision, with RSD values below 4.28% for both detection modes, confirming strong repeatability and reproducibility. Importantly, the analytical results showed no statistically significant differences from those obtained by the reference HPLC method [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], further supporting the robustness and reliability of the proposed platform for routine analysis in diverse real-world samples.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Vitamin C recovery from different real samples using colorimetric-based mode (n = 3).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eSample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eAdded\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\n \u003cp\u003eColorimetric-mode\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\n \u003cp\u003eReference method [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003et-calculated\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eRecovery (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eRSD %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eRecovery (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eRSD %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTablets (160 mg/tablet)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e143.87\u003c/p\u003e\n \u003cp\u003e146.97\u003c/p\u003e\n \u003cp\u003e150.06\u003c/p\u003e\n \u003cp\u003e153.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e103.3\u003c/p\u003e\n \u003cp\u003e103.2\u003c/p\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e138.76\u003c/p\u003e\n \u003cp\u003e141.67\u003c/p\u003e\n \u003cp\u003e144.37\u003c/p\u003e\n \u003cp\u003e148.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e97.0\u003c/p\u003e\n \u003cp\u003e93.5\u003c/p\u003e\n \u003cp\u003e94.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e3.74\u003c/p\u003e\n \u003cp\u003e3.50\u003c/p\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e2.783\u003c/p\u003e\n \u003cp\u003e2.108\u003c/p\u003e\n \u003cp\u003e3.871\u003c/p\u003e\n \u003cp\u003e3.982\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTomato juice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e18.67\u003c/p\u003e\n \u003cp\u003e21.87\u003c/p\u003e\n \u003cp\u003e24.78\u003c/p\u003e\n \u003cp\u003e29.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e106.7\u003c/p\u003e\n \u003cp\u003e101.8\u003c/p\u003e\n \u003cp\u003e103.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003cp\u003e4.10\u003c/p\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e19.76\u003c/p\u003e\n \u003cp\u003e23.01\u003c/p\u003e\n \u003cp\u003e25.87\u003c/p\u003e\n \u003cp\u003e29.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e108.3\u003c/p\u003e\n \u003cp\u003e101.8\u003c/p\u003e\n \u003cp\u003e96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e2.74\u003c/p\u003e\n \u003cp\u003e4.484.29\u003c/p\u003e\n \u003cp\u003e5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e3.928\u003c/p\u003e\n \u003cp\u003e4.013\u003c/p\u003e\n \u003cp\u003e3.398\u003c/p\u003e\n \u003cp\u003e4.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOrange juice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e36.48\u003c/p\u003e\n \u003cp\u003e39.42\u003c/p\u003e\n \u003cp\u003e42.48\u003c/p\u003e\n \u003cp\u003e47.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003cp\u003e106.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003cp\u003e3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e31.89\u003c/p\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003cp\u003e38.26\u003c/p\u003e\n \u003cp\u003e42.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e99.0\u003c/p\u003e\n \u003cp\u003e106.1\u003c/p\u003e\n \u003cp\u003e102.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003cp\u003e3.29\u003c/p\u003e\n \u003cp\u003e4.92\u003c/p\u003e\n \u003cp\u003e5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e2.873\u003c/p\u003e\n \u003cp\u003e3.011\u003c/p\u003e\n \u003cp\u003e4.178\u003c/p\u003e\n \u003cp\u003e4.180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003cp\u003e7.92\u003c/p\u003e\n \u003cp\u003e10.87\u003c/p\u003e\n \u003cp\u003e14.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e104.7\u003c/p\u003e\n \u003cp\u003e101.5\u003c/p\u003e\n \u003cp\u003e94.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003cp\u003e3.67\u003c/p\u003e\n \u003cp\u003e3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.32\u003c/p\u003e\n \u003cp\u003e8.67\u003c/p\u003e\n \u003cp\u003e11.87\u003c/p\u003e\n \u003cp\u003e14.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e111.7\u003c/p\u003e\n \u003cp\u003e109.2\u003c/p\u003e\n \u003cp\u003e95.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e4.98\u003c/p\u003e\n \u003cp\u003e5.01\u003c/p\u003e\n \u003cp\u003e4.28\u003c/p\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e4.019\u003c/p\u003e\n \u003cp\u003e3.276\u003c/p\u003e\n \u003cp\u003e3.721\u003c/p\u003e\n \u003cp\u003e4.119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003et-tabulated at confidence level 95 % and n= 3 is 4.303.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Vitamin C recovery from different real samples using fluorometric-based mode (n = 3).\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eSample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eAdded\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\n \u003cp\u003eColorimetric-mode\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\n \u003cp\u003eReference method [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003et-calculated\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eRecovery (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eRSD %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eRecovery (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eRSD %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTablets (160 mg/tablet)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e148.23\u003c/p\u003e\n \u003cp\u003e151.28\u003c/p\u003e\n \u003cp\u003e154.48\u003c/p\u003e\n \u003cp\u003e158.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e101.7\u003c/p\u003e\n \u003cp\u003e104.2\u003c/p\u003e\n \u003cp\u003e102.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e4.28\u003c/p\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003cp\u003e4.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e145.91\u003c/p\u003e\n \u003cp\u003e148.84\u003c/p\u003e\n \u003cp\u003e152.01\u003c/p\u003e\n \u003cp\u003e155.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e97.7\u003c/p\u003e\n \u003cp\u003e101.7\u003c/p\u003e\n \u003cp\u003e100.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e4.29\u003c/p\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003cp\u003e4.34\u003c/p\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e3.232\u003c/p\u003e\n \u003cp\u003e3.817\u003c/p\u003e\n \u003cp\u003e2.763\u003c/p\u003e\n \u003cp\u003e2.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTomato juice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e21.32\u003c/p\u003e\n \u003cp\u003e24.47\u003c/p\u003e\n \u003cp\u003e27.78\u003c/p\u003e\n \u003cp\u003e32.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e105.0\u003c/p\u003e\n \u003cp\u003e107.7\u003c/p\u003e\n \u003cp\u003e106.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003cp\u003e3.77\u003c/p\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e25.83\u003c/p\u003e\n \u003cp\u003e28.76\u003c/p\u003e\n \u003cp\u003e31.45\u003c/p\u003e\n \u003cp\u003e36.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e97.7\u003c/p\u003e\n \u003cp\u003e93.7\u003c/p\u003e\n \u003cp\u003e101.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003cp\u003e3.984.20\u003c/p\u003e\n \u003cp\u003e3.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e2.781\u003c/p\u003e\n \u003cp\u003e3.782\u003c/p\u003e\n \u003cp\u003e2.863\u003c/p\u003e\n \u003cp\u003e3.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOrange juice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e32.89\u003c/p\u003e\n \u003cp\u003e36.11\u003c/p\u003e\n \u003cp\u003e38.86\u003c/p\u003e\n \u003cp\u003e43.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e107.3\u003c/p\u003e\n \u003cp\u003e99.5\u003c/p\u003e\n \u003cp\u003e103.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003cp\u003e3.78\u003c/p\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e33.65\u003c/p\u003e\n \u003cp\u003e36.89\u003c/p\u003e\n \u003cp\u003e40.02\u003c/p\u003e\n \u003cp\u003e42.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e108.0\u003c/p\u003e\n \u003cp\u003e106.2\u003c/p\u003e\n \u003cp\u003e93.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003cp\u003e3.82\u003c/p\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003cp\u003e5.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e3.271\u003c/p\u003e\n \u003cp\u003e3.311\u003c/p\u003e\n \u003cp\u003e4.078\u003c/p\u003e\n \u003cp\u003e3.280\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e5.12\u003c/p\u003e\n \u003cp\u003e8.30\u003c/p\u003e\n \u003cp\u003e10.89\u003c/p\u003e\n \u003cp\u003e15.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e106.0\u003c/p\u003e\n \u003cp\u003e96.2\u003c/p\u003e\n \u003cp\u003e99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003cp\u003e4.01\u003c/p\u003e\n \u003cp\u003e3.67\u003c/p\u003e\n \u003cp\u003e3.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e5.54\u003c/p\u003e\n \u003cp\u003e8.63\u003c/p\u003e\n \u003cp\u003e11.78\u003c/p\u003e\n \u003cp\u003e14.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-----\u003c/p\u003e\n \u003cp\u003e10.3.0\u003c/p\u003e\n \u003cp\u003e104.0\u003c/p\u003e\n \u003cp\u003e94.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e3.72\u003c/p\u003e\n \u003cp\u003e4.81\u003c/p\u003e\n \u003cp\u003e5.08\u003c/p\u003e\n \u003cp\u003e4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e4.109\u003c/p\u003e\n \u003cp\u003e3.331\u003c/p\u003e\n \u003cp\u003e3.883\u003c/p\u003e\n \u003cp\u003e4.439\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003et-tabulated at confidence level 95 % and n= 3 is 4.303.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eIn summary, we have successfully developed a dual-mode colorimetric and fluorometric sensing platform for highly sensitive and selective detection of vitamin C, enabled by the robust catalytic performance of Fe and N co-doped carbon nanotubes (FeN@CNTs). The single-atom Fe\u0026ndash;Nₓ active sites within a hierarchically porous carbon framework endow the system with exceptional peroxidase-mimicking activity, enabling efficient ROS generation and catalytic turnover under mild conditions. Both detection modes\u0026mdash;absorbance and fluorescence\u0026mdash;demonstrated wide linear ranges, ultralow detection limits (0.042 \u0026micro;M and 0.003 \u0026micro;M, respectively), and excellent reproducibility across multiple batches. The smartphone-assisted readout further underscores the potential for portable, on-site applications. Importantly, the platform exhibited high operational stability and strong anti-interference capability across diverse analytes and real-world samples, including fruit juices, pharmaceuticals, and urine, with recoveries closely matching HPLC benchmarks. This work not only establishes FeN@CNTs as a powerful nanozyme-based probe for vitamin C quantification but also highlights the broader utility of single-atom catalyst architectures in next-generation biosensing technologies. Future studies will aim to expand this strategy to multiplexed analyte detection and explore surface functionalization routes for enhancing molecular selectivity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2601).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eA.M. Wu, H. Ding, W. Zhang, H.B. Rao, L.Z. Wang, Y.Y. Chen, C.F. Lu, X.X. 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Antioxidants 11 (2022), p. 134.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Scheme 1","content":"\u003cp\u003eScheme 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Single-atom nanozyme, FeN@CNTs, Dual-mode sensing, Vitamin C detection, Colorimetric and fluorometric assay","lastPublishedDoi":"10.21203/rs.3.rs-8969133/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8969133/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccurate vitamin C quantification is essential for evaluating nutritional status and supporting clinical assessment of deficiency risk, oxidative stress, and supplementation outcomes, while also enabling quality control of foods and pharmaceuticals by verifying label claims and monitoring vitamin C degradation during processing and storage. Here, we report a highly sensitive dual-mode (colorimetric/fluorometric) sensing platform based on iron\u0026ndash;nitrogen co-doped carbon nanotubes (FeN@CNTs) prepared via electrospinning, hydrothermal treatment, and carbonization. The resulting single-atom nanozyme contains atomically dispersed Fe\u0026ndash;Nₓ catalytic sites that emulate peroxidase-like activity and deliver strong catalytic performance. The assay exploits reactive oxygen species (ROS)-driven oxidation of a chromogenic reporter (TMB) and a fluorogenic reporter (Amplex Red), while vitamin C is quantified through its antioxidant/ROS-scavenging effect that suppresses signal formation in a concentration-dependent manner. Under optimized conditions, the platform achieves ultralow detection limits of 0.042 \u0026micro;M (colorimetric) and 0.003 \u0026micro;M (fluorometric), broad linearity up to 360 \u0026micro;M, and high analytical precision (RSD\u0026thinsp;\u0026lt;\u0026thinsp;5%). A smartphone-assisted RGB readout further enables rapid, portable quantification suitable for on-site screening. The FeN@CNTs sensor demonstrates strong operational stability, high selectivity, and good tolerance toward common interferents, including biothiols and polyphenols. Practical feasibility was confirmed in pharmaceutical tablets, fruit juices, and urine, affording recoveries of 94.5\u0026ndash;107.7% and results statistically consistent with a reference HPLC method. Collectively, these outcomes position FeN@CNTs as a robust single-atom nanozyme platform for real-time vitamin C analysis with potential impact in food safety surveillance, clinical testing, and point-of-care sensing.\u003c/p\u003e","manuscriptTitle":"Electrospun FeN@CNT single-atom nanozyme for triple-mode ROS-mediated colorimetric and fluorometric detection of vitamin C","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-25 08:55:28","doi":"10.21203/rs.3.rs-8969133/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6908473c-9ef6-4306-bdd6-e2e4e9c273c3","owner":[],"postedDate":"March 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T09:56:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-25 08:55:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8969133","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8969133","identity":"rs-8969133","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}